In this paper, we propose the task of creating a generative model from just a handful of hand-drawn sketches. Ever since Ivan Sutherland's SketchPad [1]}, computer scientists have recognized the usefulness of guiding computer-generated content using sketching interface. This tradition has continued in the area of sketch-based image synthesis and 3D modeling [2]}, [3]}, [4]}. But rather than creating a single image or a 3D shape from a sketch, we wish to understand if it is possible to create a generative model of realistic images from hand-drawn sketches. Unlike sketch-based content creation, where both the input and output are 2D or 3D visual data, in our case, the input is a 2D sketch and the output is a network with millions of opaque parameters that control algorithm behavior to make images. We ask: with such a different output domain, which parameters shall we update, and how? How do we know whether the model's output will resemble the user sketch?
